Historically, to arrive at a set of targets for the placement of wells for the extraction of hydrocarbons, a manual process is used in which the surfaces representing the top, bottom surface, or intermediate surface of the reservoir is interpreted from seismic data to place the targets. In this process, the surface is overlaid with a color-coded attribute overlay, which may be comprised of attributes indicating the porosity, permeability, saturations, or other characteristics of the reservoir. Based on the color-coded attributes, the target locations are visually selected, the attribute color coding being the primary indicator of the target location.
In the above method, since the color coding is used as the primary cue for target location, it is very difficult to take into consideration the drainage radius and an entire three-dimensional model of a reservoir, because only the attributes of a surface are being considered. To take into consideration the entire three-dimensional model of the reservoir, this method would entail sequentially evaluating adjacent layers of the reservoir until the entire reservoir is completely evaluated, while attempting to remember the attributes associated with each of the previous layers. This a very tedious and time consuming process.
In another historically used and more accurate method than the above, the raw seismic data is visually analyzed for so called “bright spots.” The bright spots are basically high or low amplitude attribute areas indicative of the porosity, permeability, saturations, or other characteristic of the reservoir. In this process, a geocellular model of the entire reservoir is created rather than evaluating a selected horizontal surface of the reservoir and filtering the model to only display the areas or “bright spots” that have certain desirable attributes. In similar fashion to the previous method, in this method, the targets are also manually selected on the resulting geobodies. This is also a time consuming and inaccurate method of locating targets.
Therefore, there is a need for an automated method for locating targets for a hydrocarbon reservoir. A method where a user sets a series of filters for processing a three-dimensional geocellular model, an expected drainage radius for each target, and the maximum number of allowable targets. Then a computer implemented method traverses the geocellular model targeting areas that meet the filtering criteria and target spacing constraints. The method may eliminate overlapping targets; therefore, the method may optimize the location of each target by optimizing the cells that are targeted. If more target areas meet the filtering and spacing criteria than the maximum allowable number, the method may only display targets in the most desirable areas by evaluating the cells under each target both horizontally and vertically and weighing each target location.
This automated process would be more desirable than the process discussed above of interpreting a surface of the reservoir, because the entire three-dimensional model of the reservoir may be taken into account, and the implemented selection process results in a more accurate selection of desirable target locations than the human selections based on visual inspection of the attributes overlaid on the surface. Furthermore, this automated process would be more accurate when compared to the method using the geocellular model, because the spacing radius may be optimized and the targets are weighted based on the cells under each target so that the placement is much more optimized than if done by human analysis. This automated process may result in an increase in accuracy and substantial time savings in the process of locating targets for well placement.
Embodiments of the present invention are directed at overcoming one or more of the above deficiencies described in the art.